Prophet
The forecasting tool every analyst has met
Latest: v1.4.0 (August 2026) — dropped Python <3.10, added full static typing and uncertainty propagation for extra regressors
Time-series forecasting library from Meta's Core Data Science team (2017), fitting additive models with trend, seasonality and holiday effects so analysts can produce credible forecasts without stats PhDs. Available in Python and R, it remains one of the most widely used forecasting tools in industry and is still actively released.
Why it matters
Let analysts produce credible time-series forecasts with trend, seasonality and holiday effects without a statistics PhD. Released in Python and R in 2017, it remains one of industry's most widely used forecasting tools and is still actively maintained, with v1.4.0 in August 2026 adding full static typing.
Facts
- Roughly 19k GitHub stars and on the order of a million PyPI downloads a month nearly a decade after release; the 'Forecasting at Scale' paper is a citation staple in business analytics.
Try it yourself
Quick start (Python and R) ↗ prophet on PyPI ↗ prophet on CRAN ↗
Sources
GitHub · prophet ↗facebook.github.io ↗peerj.com ↗